Web Reference: Sep 13, 2022 · In this work, we estimate the density of potential outcomes after interventions from observational data. For this, we propose a novel, fully-parametric deep learning method called Interventional Normalizing Flows. In this vein, we present the Normalizing Flow Network (NFN), a neural network based, parametric CDE model using NFs as its density model. Given enough capacity, NFNs allow us to model highly complex conditional densities. This thesis proposal is focused on understanding normalizing flows for density estimation in detail, both theoretically and empirically.
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